CHAPTER IV

VARIABLES. HYPOTHESES AND METHODOLOGY

DESIGN OF THE STUDY

VEFUABLES OF THE STUDY

TOOLS USED FOR MEASUREMENT

DESCRIPTION OF TOOLS

SAMPLE USED FOR THE STUDY

COLLECTION OF DATA

SCORING AND CONSOLIDATION OF DATA

STATISTICAL TECHNIQUES USED

DESCRIPTION OF THE STAISTICAL TECHNIQUES USED

OTHER DETAILS RELATING TO THE DESIGN

VARIABLES, HYPOTHESES, AND METHODOLOGY

This chapter deals with the methods and procedure followed in the

study. These include the design of the study, the variables, selection of

sample, description of the tools used, data collection and statistical

techniques made use of.

4.1.0. DESIGN OF THE STUDY

The study was conducted in three phases. The first phase includes

the selection of variables involved in the study and construction and

validation of tests to measure them. In the second phase, the sample

was selected and data were collected regarding the variables. In the

third phase the data were analysed by using suitable statistical procedures

and the conclusions drawn. in The diagrammatic representation of the

design of the study is given below :

TABLE 4.1 T H E DIAGRAMMATIC REPRESENTATION O F T H E

PHASE ONE

PHASE TWO

PHASE THREE

DESIGN O F T H E STUDY

This phase involved

a) the selection of variables

b) the formulation of hypotheses

c) selection of appropriate tools to measure the

following:

i) Intelligence

ii) Home Environment for Science Learning

iii) School Learning Environment

iv) Socio-economic Status

v) Parental Education

vi) Parental Occupation

vii) Parental Income

d) preparation of tools with psychometric

properties to measure the following :

i) POP

ii) Attitude towards Science Learning

iii) Science Learning Interest

a) selection of sample

b) collection of data

statistical procedures used to analyze the data

4.2.0. VARIABLES OF THE STUDY

The study is designed with POP as the dependent variable and a

select group of cognitive, affective, social and environmental variables

treated as independent variables.

The details relating to the variables of the study are presented

below :

4.2.1. DEPENDENT VARIABLE

Process Outcomes in Physics (POP). The major component abilities

of Process Outcomes in Physics (POP) as used in the study are :

i) recognizing and defining a problem

ii) formulating hypothesis

iii) collecting data

iv) interpreting data

V) evaluating hypothesis

vi) formulating generalizations

4.2.2. INDEPENDENT VARIABLES

Four broad groups of variables - cognitive variables, affective

variables, social variables, and environmental variables have been

included as independent variables of the study. The details of the different

variables under each major group are given below :

1. Cognitive variables

i) Cognitive variables used in the study are restricted to one

crucial variable, viz., Intelligence

2. Affective variables

Affective variables used in the study a re :

ii) Attitude towards Science Learning

iii) Science Learning Interest

3. Social variables

iv) Parental Education

v) Parental Occupation

vi) Parental Income

vii) Socio-economic Status

4. Environmental variables

viii) Home Environment for Science Learning

ix) Science Learning Environment-student initiated

x) Science Learning Environment-teacher provided

xi) Total Science Learning Environment

4.2.3. CRITERIA USED FOR SELECTING T H E INDEPENDENT VARIABLES

Variables which registered correlation with educational outcomes

in process tests in physics or product outcomes were scrutinized.

Reported studies relating to the variables influencing process outcomes

in different science subjects were also scrutinized. The selection of

independent variables was done on the basis of research evidence relating

these variables and dependent variable of the study or in some cases as

having a significant association with conventional outcomes in science

subject. Some additional considerations were also weighed in selecting

the independent variables for the study. The additional considerations

of this kind are :

i variables selected for the study should specifically fall into the

four major groups selected, viz., cognitive, affective, social or

environmental groups

ii variables selected should show significant association with

Process Outcomes in Science or conventional achievement in

science, either as a direct correlation or as an indirect cause-

effect relationship

iii the selected variables should be capable of being quantified

and lend themselves to objective group measurement

iv standardized tests should as far as possible, be available for

measuring the variables selected

v wherever standardized tests are not available, it should be

possible to develop psychometric tools within a reasonable

time.

The review of research studies reported earlier and the above criteria

were used simultaneously for identifying the variables.

4.3.0. TOOLS USED FOR MEASUREMENT

The following tools were used for the collection of data.

1. Test of Process Outcomes in Physics-TPOP-(to measure the

dependent variable).

2. The Kerala Non-Verbal Group Test of Intelligence for

Secondary Schools (to measure intelligence).

3. Scale of Attitude Towards Science Learning-SATSL-, (to

measure attitude towards science learning).

4. Science Learning Interest Inventory-SLII-, (to measure science

learning interest).

5. General Data Sheet (to measure Parental Education, Parental

Occupation, Parental Income and SES).

6 . Home Environment Inventory for Science Learning (to measure

Home Learning Environment).

7 . Science Learning Environment Inventory (to measure Science

Learning Environment-student initiated, Science Learning

Environment-teacher provided and Total Science Learning

Environment).

4.4.0. DESCRIPTION OF THE TOOLS

The details of the tools used to measure different types of variables

are given below.

4.4.1. TEST OF PROCESS OUTCOMES IN PHYSICS (TPOP)

The investigator with the help of her supervising teacher, developed

and standardized 'Test of Process Outcomes in Physics (TPOP) in order

to measure the dependent variable, Process Outcomes in Physics (POP).

The Process Outcomes in this test were operationalized on the basis of

the theoretical models developed by Obourn (1960) and Klopfer (1971)

and on the basis of consultation with experts in field of science teaching.

The investigator selected six major skills and sixteen sub-skills coming

under them to be used for developing Test of Process Outcomes in

Physics (TPOP). The details of the skills and sub-skills used for the

preparation of test are presented in the table 4.2.

TABLE 4.2 SKILLS AND SUB-SKILLS USED FOR MEASURING PROCESS

OUTCOMES.

1 .0 . Recognizing and defining a problem

1.1. Pupils recognize specific problem in a new situation

1.2. Pupils isolate the single major idea of a problem

1.3. Pupils state problem as definite and concise questions

2.0. Formulating hypothesis

2.1. Pupils suggest tentative solutions to the problem

3.0. Collecting data

3.1. Pupils select suitable test of the hypothesis

3.2. Pupils design experiment

3.3. Pupils select equipments for experiment

3.4. Pupils observe objects and phenomena

3.5. Pupils measure objects and changes

4.0. Interpreting Data

4.1. Pupils organize data collected

4.2. Pupils identify relationships

4 .3 . Pupils interpret relationships

5.0. Evaluating hypothesis

5.1. Pupils formulate conclusions, on the basis of relationships

found

5.2. Pupils evaluate hypothesis in relation to the data interpreted

6 . 0 . Formulating generalizations

6.1. Pupils apply conclusions to new situations

6 . 2 . Pupils formulate generalizations on the basis of relationship

identified and conclusions formed and applied.

PREPARATION OF ITEMS

Since the Purpose of the TPOP was to measure the Process in

outcomes Physics achieved by the secondary school students of Kerala,

the items prepared were from the area of secondary school Physics.

The investigator took precautions to include the items, which have

practical applications in day-to-day life. Special care was given so that

the mental operation while answering the questions were the natural

outcomes of science teaching and learning in classroom situatioiis.

The following books and other forms of literature were freely used

as guidelines for preparing the test items.

1. Science Teaching and Testing (Nedelsky, 1965).

2. Handbook of Formative and Summative Evaluation of Students

Learning (Bloom, et. a]., 1971).

3. Science Education in Nineteen Countries-An Empirical Study

(Comber and Keeves, 1973).

4. Integrated Process Skills Test (Okey & Dillashow, 1979).

5. Middle Grades Integrated Process Skill Test (Padilla & Cronin,

1978).

6. Test of Process outcomes in Biology (Suresh, 1991)

7. Text Books in Physics for Standards VII, VIII and IX (Govt. of

Kerala, 1 9 9 2 & 1994).

The TPOP include six subtests. Each subtest measures the

acquisition of each major skill given in table 4.2. Each subtest contains

fifteen items of objective multiple choice type. For each item, four

alternative responses are given. The respondent has to select the correct

alternative. The choice of correct alternative by the respondent would

indicate that he/she has achieved the outcome in question. The

explanations given below regarding each skill served as guidelines for

the preparation of the items.

i) Recognizing and Defining a Problem

The test items under this head present problematic situations before

the respondent. The respondent has to identify the problem area, he

has to isolate the single major idea of a problem, and has to define the

problem using correct language.

ii) Formulating Hypotheses

In this subtest the subject is presented stated problems. He has to

suggest suitable solutions to the problem in hand, based on the conditions

presented in the items. The hypothesis should direct one to further

investigation. Four alternative hypotheses were given along with each

test item. The task of the subject is to decide which hypothesis is the

most suitable and reasonable one.

i i i ) Collecting Data

In this subtest, students are given actual learning situations for

particular problems. The tasks of the students are to identify the

manipulated variables, the responding variables and controlled variables

in the problem situations and to describe how variables are controlled.

The correct response to items under this category would indicate that

the student has attained the outcome in question.

iv) Interpreting Data

Here, the tasks assigned to the respondent are to describe the

collected data in verbal or nonverbal form, organize the data so as to

facilitate effective communication, to draw inference based upon the

collected data and to construct tables.

v) Evaluation of Hypotheses

In this subtest, the problem stated and the hypotheses formulated

are presented to the subject. He has to design an investigation for testing

the hypothesis, to select suitable test from the alternate tests given and

to evaluate the hypotheses on the basis of the given data. [The student

has to s ee whether t he evidence is consistent with t he logical

requirements of the hypothesis.]

vi) Formulating Generalizations

Here the tasks given to the respondent are to apply the conclusions

to new situations and formulate generalizations on the basis of

relationships identified.

Twenty items each were pooled initially for each subtest. Some of

the test items were adapted from school Physics text-books, published

texts and from the available literature cited earlier. A panel of physics

teachers was formed for establishing the face validity. Each item was

discussed at length in terms of its appropriateness, complexity, subject

matter and exactness of information. Based on the scrutiny of experts,

f if teen items were selected for each subtest, which were found

appropriate and valid. These subtests constitute the draft TPOP.

Instructions for the respondents, scoring key and appropriate form of

the response sheet were prepared.

The draft TPOP was 'pretriedout' to a group of 1 0 students of

ninth standard randomly selected from St. Thomas High School, Pala

in order to ensure the clarity of the wordings and directions.

Based on the pre-tryout, final draft TPOP consisting of ninety items,

fifteen items for each subtest was prepared and got printed.

Standardization of TPOP

The draft test was administered to a representative sample of 400

students drawn from standard IX of the secondary schools of Kottayam,

Kannur and Malappuram districts. The testing was done during the

academic year 1996-'97. One score each was given to the correct

response of each test item. The sum of the scores for the ninety items

was taken as the total score for the test. After rejecting incomplete

entries, only 3 7 8 answer sheets were available for item analysis. Further

eight answer sheets were rejected at random in order to bring down the

number to 370, to follow the psychometric procedures for item analysis.

The 370 answer scripts were arranged in the descending order of

the total score. The highest 27% and the lowest 27%, with respect to

the total scores were separated. There were 1 0 0 response sheets each

from upper and lower levels.

Each response sheet in the upper and lower level was examined.

The number of respondents in the upper and lower groups who answered

each item correctly was found out. The indices of item discrimination

and difficulty were estimated by using the procedure suggested by Ebel

(1965).

The difficulty level and discriminating power of each item were

estimated using the following formulae

u + L x l o o Index of item difficulty Dv = -- 2N u - L

Index of discrimination Di = -- N

Where

'U ' = the number of correct responses for any item in the upper

group.

'L' = the number of correct responses for any item in the lower

group.

' 2N ' = total number of answer scripts in the upper and lower levels.

'N ' = 100 , since the upper and lower groups stands for 27% of

the total group of 370 which is equal to 1 0 0 for both upper

and lower groups.

The item analysis data is given as Appendix I

On the basis of the indices of difficulty and discrimination, items

were rated. Items with difficulty index between 65 and 35 (on the

assumption that the items of difficulty level of 5 0 have the highest

discriminating power) were identified. From among these items, items

with highest discriminating power were selected. Only items of

discriminating power of 0.30 and above were selected for the final test.

Thus 10 items from each subtest were selected and they were arranged

in the increasing order of difficulty.

The final TPOP included a covering page with specific directions

for the guidance of the students and the six subtests containing 1 0

items each were got printed in the shape of a test booklet.

The draft and final TPOP are given as Appendices I1 & 111. The

response sheet and scoring key are provided as appendices IV & V,

the table of norms (percentile norms) for the test (worked out for the

final sample of 900) are presented as Appendix VI. The English

translation of final test is given as Appendix VII.

Validity and Reliability of TPOP

Content validity of the test, which requires the determination of

the adequacy of each item to be a sample of the process skills which

are supposed to be measured, was ensured through careful planning of

the test, satisfying the adequacy of sampling of test items by following

the standard theoretical models of the construct to be measured and

meticulous analysis of the test items by experts. In the final TPOP, all

the six subtests were given equal weightage by including equal number

of items in each.

The construct validity of the test was estimated using average marks

obtained in Physics for the first and second terminal examination, of

standard IX pupils treated as the external criteria. The average marks

in physics of 1 0 0 pupils of standard IX was used for this purpose. The

scores obtained in the TPOP were correlated with the average physics

scores. The coefficient of correlation was found to be 0.77.

The split-half reliability was estimated for the whole test as well as

for the component tests. The coefficient of correlations corrected for

shortening using Spearman Brown formula are presented in Table 4.3.

TABLE 4.3. RELIABILITY COEFFICENTS CORRECTED USING SPEARMAN.

BROWN FORMULA FOR THE TPOP

Tests Reliability coefficient

Subtest I .92

Subtest 11

Subtest 111

Subtest IV

Subtest V . 9 2

Subtest VI

Whole test

Reliability using Kuder - Richardson formula was estimated.

The reliability by using this method (for N= 100) was found to be

0 .96 .

The validity and reliability coefficients reported here show that

TPOP used in the study is a reasonably valid and reliable tool for

measuring POP.

4.4.2. SCALE O F ATTITUDE TOWARDS SCIENCE LEARNING (SATSL)

This scale was developed by the investigator with the help of her

supervising teacher, inorder to measure the attitude of secondary school

students towards learning science. Attitude towards science learning is

the favourable or unfavourable disposition of the individual towards the

learning of science, which cannot be directly observed, but can be

inferred from overt behavior.

Since the investigator couldn't find an attitude scale which measures

the attitude of secondary school students towards science learning which

was meant for Indian sample, she, with the help of the supervising

teacher h z i s 4 constructed an attitude scale, namely Scale of Attitude

towards Science Learning (SATSL) applicable to the secondary school

students of Kerala state.

SELECTION OF STATEMENTS

After consulting with experts in the field and teacher educators, it

was decided to use the technique developed by Likert. The selection of

statements was done as follows.

The investigator reviewed books, periodicals, and other descriptive

materials to procure the material to construct the statements for the

attitude scale. Experts in the field were also consulted and their

suggestions were taken into consideration. It was decided to include

three dimensions of attitude towards science learning. These were views

on science learning, attitude towards scientists and the contributions of

science, and views on science as a process.

An initial pool of 60 statements was prepared. This pool of

statements was given to ten experienced and qualified teachers. Before

this the language was checked for ambiguity of wordings, if any. It was

also ascertained that the vocabulary used in the test item was appropriate

for secondary school students. The panel of teachers were asked to

evaluate the statements keeping in mind the following points :

1). whether there were enough statements under each of the

attitudinal dimension

2). accuracy and relevance of each statement

3). the level of language used for each statement

Based on their suggestions, those statements, which were complex,

vague, over-generalised, and not appropriate to measure the attitudinal

construct, were deleted. The remaining 4 0 statements formed the draft . -

form of the attitude scale

Out of the 4 0 statements 20 were of positive polarity and remaining

20 were of negative polarity. 14 statements were to rate the views on

science learning, 14, to rate the views on science as a process, and 1 2

to rate the attitude of the respondent towards scientists and their

contributions to science.

INITIAL TRY OUT

The 4 0 statements were arranged as in Likert type. To avoid any

error or tendency to a stereotyped response, items of positive polarity

and negative polarity were evenly arranged. Directions for the

respondents were also prepared. The students were asked to assign

any one of the five categories after carefully reading the statement.

The five categories were SA-strongly agree, A-Agree, U-undecided,

D-disagree and SD-strongly disagree. After the administration of the

scale, it was scored by keeping into consideration the scoring procedure

suggested by Likert, (Edwar+,1957)

for every S. A response 5

A response 4

U response 3

D response 2

S . D response 1

For items of negative polarity, the scoring system was reversed.

Appropriate response sheet was also prepared along with the draft form

of the scale.

ITEM ANALYSIS

The draft scale was administered to a representative sample of

1 8 0 ninth standard students. The sum of the scores of all the items

constituted the total score of the scale. 1 4 , incomplete entries were

exempted and the rest of 6 entries were rejected at random to bring

down the number to 160 for convenience.

The selection of items for the final form of scale, SATSL was done

as per the procedure suggested by Edwards (1957). The response sheets

of the individuals are arranged in the descending order of the total scores.

The highest 25% and the lowest 25% of the response sheets were

separated (N, = 4 0 and N, = 40). These were criterion groups in terms

of which to evaluate the individual statements. In evaluating the responses

of the high and low groups to the individual statements, the ratio was

found out using the formula,

where

XH = the mean score on a given statement for the high group - - the mean score on the same statement for the low group XL -

n = the number of subjects in the upper and low groups

X, = score for a given statement in the high group

X, = score for a given statement in the low group

The 't' value for each item was calculated by using the same formula.

The statements for which 't' value is grater than or equal to 1 .75 was

regarded as an item which possesses internal consistency and hence

discriminating power (Edwar&,1957). Items with 't' values from 3.02

to 6.60 were selected for the final form of the scale.

Thus 2 5 statements were selected for the final test. Out of the 2 5

statements, 13 were of negative polarity and 1 2 were of positive polarity.

Items with negative and positive polarity were distributed evenly in the

decreasing order of difference in means.

FINAL FORM

The final form of the SATSL contained 2 5 statements and specific

directions for the respondents. An appropriate response sheet was also

prepared. The scoring procedure for the items of positive polarity is as

follows :

for every S A response 5

A response 4

U response 3

D response 2

S D response 1

For the items of negative polarity the scoring procedure is as follows

for every S A response 1

A response 2

U response 3

D response 4

S D response 5

An illustrative item is given below.

There is no fault in doing other helpful matters in lieu of science

classes.

Since 'SD' is encircled, the score of the item is 5

The maximum and minimum scores, which the students may score

on SATSL, will be 1 2 5 and 25 respectively.

The construct validity of SATSL was estimated by using average

marks obtained in Physics, Chemistry and Biology for the first and second

terminal examinations of standard 1X pupils.The average marks in science

of 100 ninth standard students were used for that purpose. The score

obtained in the SATSL was correlated with achievement in science.

The coefficient of correlation was found to be 0.79.

The reliability of SATSL calculated by using split-half method and

corrected by using Spearman-Brown prophecy formula was found to be

0.87. The reliability of scale, calculated by test-retest method was found

to be 0.86. The high validity and reliability coefficients thus obtained

show that the scale is a reasonably valid and reliable one.

The Item analysis details SATSL are given as appendix VIII, The

draft form and final form of the scale are given as Appendices IX and X

respectively. The English translation of the final scale is given as appendix

XI and the percentile norm is given as appendix XII.

4.4.5. SCIENCE LEARNING INTEREST INVENTORY (SLII)

The investigator developed a Science Learning Interest Inventory

(SLII) for the purpose of measuring interest of secondary school students

towards science learning. The details of the procedure involved in the

development are given below.

PREPARATION OF THE INVENTORY (DRAFT FORM)

Items in the inventory were presented in the form of triads and the

respondents were required to choose one of the three alternative

activities grouped under an item. It thus employed forced choice triad

type technique on the assumption that it reduces social desirability,

reduces bias, and the validity under forced choice technique is stable

over a period of time.

The investigator selected various activities, which have direct

relation with various school subjects. The activities were categorized

and put in each item on the basis of their nature as far as possible.

Each item included three activities. The task of the respondent was to

select the activity, which he/she likes the most. The items were prepared

in a way that out of the three activities, one is related to science and

the rest related to humanities. 6 0 items were prepared and subjected to

scrutiny by a panel of three experts. The items which were judged as

powerful to reflect the students' interest towards learning of science,

were selected. 30 items were selected for the draft inventory. Directions

for the respondents also were prepared along with the draft. The students

were asked to choose the activity, which was more preferred by them

than other activities in each item.

ITEM ANALYSIS

The inventory (draft form) was administered to a sample of 400

students of standard IX. For each item, i f the respondent selected the

activity showing some inclination towards the learning of science, 'one'

score was assigned and a 'zero' score for choosing other alternatives.

The sum of the scores of the 30 items constituted the total score of the

inventory. From the 400 responses, ten incomplete response sheets

were rejected and 390 response sheets were made available for item

analysis. 2 0 more response sheets were rejected randomly for bringing

down the number to 370, for the sake of convenience. The response

sheets were arranged in the descending order of scores. The performance

of the upper and lower 27% of the sample forming criterion groups,

compared to yield discriminating indices for 3 0 items.

The discriminating power of each item was calculated by applying

the formula given by Ebel (1965)

u - L Di = -----

N

Where 'Di' stands for Discriminating index (upper lower index)

'U' stands for number of respondents who select activities

related to science in upper group

'L' stands for the number of respondents who select activities

related to science in the lower group

' N ' stands for the number of respondents in each group

The data showed that all the items have significant discriminating

power. Even though, for ensuring the better quality of the inventory,5

items which have low discriminating index were rejected. Thus the final

inventory consisted of 2 5 items.

FINAL FORM OF T H E INVENTORY

In the final form of the inventory, 2 5 items in all, which possess

high discriminating power, were included. For each item 'one' score

was given, if a subject select the activity which shows some inclination

towards the learning of science and a 'zero' score for selecting other

alternatives. Thus a respondent could get a maximum of 2 5 scores in

this Inventory.

An illustrative item is given below:

Select one activity, which you like the most, from the set of three

activities given below, and put a cross mark in the proper column in the

response sheet.

A. Improvise a thermometer

B. Study the different methods of sculpture

C. Record speeches at public meetings

Since the cross mark is below 'A ' , it shows that the respondent

has interest in science learning than the other two activities. Hence a

score was assigned to that response.

Item number -

1

VALIDITY AND RELIABILITY O F T H E INVENTORY

The content validity of the inventory was ensured by subjecting the

items prepared for the initial tryout before a panel of 10 experts for

scrutiny. The items, which were certified by the experts as effective for

measuring science learning interest, were selected.

The construct validity of SLII was estimated by using the average

marks for science for the first and second terminal examinations, and

the validity coefficient was found to be 0 .72 ; (for N = 100)

A

X

B C

The reliability coefficient measured by test-retest method was 0.94.

The reliability coefficient estimated by using split-half method and

corrected by using Spearman-Brown prophecy formula was = 0.81 and

that by using Kuder Richardson formula was 0 .96 (for N = 40).

The opinion of the experts' high discriminating power and high

reliability and validity coefficients show that the inventory possesses

satisfactory psychometric properties.

The draft and final forms SLII and the English translation of its

final form are given as appendices XIII, XIV, and XV. The item analysis

data is given as appendix XVI. The percentile norm of Science Learning

Interest Inventory is given as appendix XVII.

4.4.4. GENERAL DATA SHEET

The investigator made use of a standard form of General Data

Sheet to collect basal information about respondents and to measure

the following variables, Parental Education, Parental Occupation,

Parental Income, and Socio-economic Status. A copy of the General

Data sheet used for the study is given as appendix XVIII.

The General Data sheet consisted of four sections. Section one

elicits the general information about the respondent (name of the

respondent, locality, age, sex, and name of the school etc.) Section two

is for collecting information regarding level of education of parents,

siblings and other members in the subject's family. Section three provides

information regarding the type of occupation of the parents and other

members in the family. Section four provides the details relating to the

income of family members. The school records were used for checking

the correctness of information entered in the General Data Sheet. The

details, which were not available in the school records, were collected

through direct questioning of the respondent during administration of

the test.

The information collected though the general data sheet helped to

classify subjects on the basis of Parental Education, Parental Occupation

and Parental Income.

4.4.5. THE KERALA SOCIO-ECONOMIC SCALE

The investigator used the Kerala Socio-Economic Scale developed

and standardized by Nair (1976), with necessary modifications (in scoring)

to measure the socio-economic status of the subjects. The Data needed

for the scale was obtained from General Data Sheet administered to

the subjects.

In this study Socio-economic Status is measured in terms of Parental

Occupation, Parental Education and Parental Income. Each of them is

divided into categories on the basis of the scoring scheme, revised by

the author (1996). Since scoring of income levels was based on old

classification, this revision was inevitable. The revision was done on the

basis of present salary pattern and cost-of-living index.

The details regarding the categories, scoring systems and

weightages are showed in Table 4.4

TABLE 4.4. CATEGORIES AND RESPECTIVE WEIGHTAGES OF THE

COMPONENTS OF THE KERALA SOCIO-ECONOMIC SCALE

CLASSlFlCATlON OF OCCUPATIONS

1. Unemployed : No permanent employment, and no special

qualifications or skills.

2. Unskilled : Coolies, ordinary labourers, watchmen, peons

and other low-level employees in establishments

and similar categories.

3. Semiskilled : Farmers , small scale merchan t s , l ibrary

attenders, office attenders.

Educational Categories score

1 . Illiterate 5

2. Standard I to IV 1 0

3. Standard V to VII 15

4. Standard Vlll to X 2 0

5 . Pre-University/Pre-Degree/

T.T.C./lntermediate 2 5

6 . B.A.,B.Sc.,B.com., Engi-

neering Diploma etc. 3 0

7 . M.A./M.Sc./M.B.B.S.,M.Ed./

B.Sc.(Engg)/B.Sc.(Tech)/

L.L.B. 3 5

Occupational Categories score

Unemployed 5

Unskilled 1 0

Semi-skilled 15

Skilled 20

Semi-Professions 3 0

Full Professions 4 0

Income (monthly) score

- Below Rs.1000/- 5

Rs.1001/- 2000/-10

2001/- 4000/- 15

4001/- 7000/- 2 0

7001/- 10000/- 2 5

10001/- 25000/-30

above 25000/- 3 5

4. Skilled : Mechanics, fitters, field workers, electricians,

dr ivers , pho tog raphe r s , lab ass i s tan ts ,

carpenters, masons, document writers, vakil

clerks, head constables, village officers, and

similar categories.

5. Semi-Professionals: Chemists, druggists, qualified nurses, trained

teachers, managers, superintendents of offices,

smallscale land-owners, sub-inspectors of police/

equivalent, sub-registrars, assistant educational

officers, block-development officers, officers of

the sub-district level, public health workers and

similar categories.

6. Full Professionals : Ministers, judges, bank executives and officials,

doctors, engineers, lawyers, university teachers,

heads of research organizations, heads of Govt.

departments, secretaries to government, high

land owners and business executives and

equivalent categories.

Each subject was assigned score on each of the three subdivisions-

Parental Education, Parental Income and Parental Occupation. The three

independent scores added (with equal weights given to each) yielded

score on the Socio-economic Status for the family or for the respondent.

4.4.6. THE KERALA NON-VERBAL GROUP TEST OF INTELLIGENCE

To measure the intelligence of the subjects, the Kerala Non-Verbal

Group Test of Intelligence was used. This is a standardized group test

of intelligence developed by Nair (Nair, 1968) for the purpose of

appraising the general intelligence of secondary school pupils of Kerala.

The test provided a single score of general intelligence yielded by adding

the scores obtained in the four subtests.

The test battery consists of four subtests; Figure classification,

Figure series, Figure analogies, and Figure matrices. The details are

given in Table 4.5.

TABLE 4.5. TEST COMPONENTS AND OTHER DETAILS OF THE KERALA

NON-VERBAL GROUP TEST OF INTELLIGENCE.

DESCRIPTION OF SUBTESTS

i) Figure classification: This test measures the ability to perceive

relationship. This consists of five figures, four of which can be

Time limit in minutes.

5

5

5

5

grouped together according to some common rule. One figure will

not go with the group. The respondent has to identify this figure,

which will not fit in the group.

No. of items inclu- ding practice items

20

2 0

2 0

20

Subtest Number

I

I1

Il l

IV

An illustrative item is presented below:

Test Component

Figure classification

Figure series

Figure analogies

Figure matrices

The correct answer is E

There are twenty items in the subtest. Out of twenty, first four

items are practice items. The answers are also given along with the

test. The remaining 16 items are used for scoring. The subject has to

work out the sixteen items within the specific time limit of five minutes.

One score is given for each correct response.

ii) Figure series.

Each item of this subtest consists five small squares arranged in a

row. The first four squares contain small figures within, while the last

square is blank. The subject has to findout the figure from four alternative

answers given, which when placed in the blank square will complete the

design. The task of the subject is to identify the rule behind the four

figures and to findout the fifth, which follows the same rule from the

alternative answers given. An illustrative item is given below :

Problem Answers

A B C D

The correct answer is D

There are 4 practice items. The remaining 16 items are to be

answered in 5 minutes. One score is given for each correct response.

iii) Figure analogies

In each item of this subtest there are four squares in a row, arranged

into two sections. They are divided into two groups of two on the left

and two on the right. The first square in the right pair contains figures

and the second square is blank. The figures contained in the first pair

on the left imply a relationship. The same relationship is assumed to

hold for the pair of squares on the right as well. The subject has to find

out the relationship connecting the figure in the first two squares and

apply it to visualise the figure which when put in the blank square on

the right would imply the same relationship. The answer is to be selected

from a set of four alternatives given.

An illustrative item is presented below :

Problem Answers

The correct answer is C.

There are 16 items to be answered in 5 minutes.

iv) Figure matrices.

Each of the items of this subtest has nine squares arranged in the

form of 3 rows and 3 columns. The matrices of nine squares with the

figures inside form one design. The design is incomplete because the

bottom right-hand corner is left blank. The subject is asked to examine

the squares in each row or column and find out the relationship

connecting the figures in the first and second rows or columns. He has

to use this relationship to find out the figure that fits in the blank square

of third column (row), from a set of four alternative answers given.

An illustrative item is given below :

Problem

Answers A B C D

The correct answer is D.

There are 16 items in this subtest to be answered in 5 minutes

SCORING

The test is scored by assigning one score for correct answer.

Separate total for each subtest can be obtained and then the scores on

the four subtests are combined to yield the total score for non-verbal

group test of intelligence.

VALIDITY AND RELIABILITY O F TEST BATTERY

Validity: The validity of the test has been assessed using different tests

as external criteria. (Nair, 1971). Validity coefficient using Progressive

Matrices Test (PMT) as external criteria, r = 0.784 (for N=256) , with

Kerala Verbal group Test of Intelligence as external criteria, r = 0 . 5 2

(for N=504) and with total marks in S.S.L.C. Examination, r = 0.537

(for N= 324). Factor analysis of the battery with the Progressive Matrices

Test and Kerala Verbal Group Test of Intelligence as reference tests,

revealed the presence of a major general factor of intelligence in all the

tests of the battery.

Reliability

Test retest reliability of the test has been calculated with different

intervals in testing. For three months interval between tests, reliability

= 0.76 (for N = 246); one month interval between tests, reliability =

0.75 (for N = 124) and for one-week interval between tests, reliability

= 0.80; (for N = 121) .

Corrected split-half coefficient for the whole test battery and for

the component tests (for N= 237) are given in Table 4.6.

TABLE 4.6. SPLIT-HALF RELIABILITY COEFFICIENTS O F THE KERALA

NON-VERBAL GROUP TEST O F INTELLIGENCE.

Corrected value of reliability coefficient.

0 .92

0 .90

0 .88

0 . 8 8

0 .91

SI.No

1.

2.

3.

4.

Subtests

Figure classification

Figure series

Figure analogies

Figure matrices

Whole Test

Reliability estimated by the rational equivalence method was

0 .864 (for N= 100).

The values quoted above show that the test is a reliable and valid

instrument for measuring the general factor of intelligence, and could

therefore be treated as an appropriate tool for the purpose of the

investigation.

4.4.7. H O M E ENVIRONMENT INVENTORY FOR SCIENCE LEARNING (HEISL)

The learning environment provided by the parents and other

members of the subjects' family for the attainment of maximum learning

in science was measured by using Home Environment Inventory for

Science Learning. This questionnaire was developed and standardized

by Suresh (1 988).

This inventory contains 25 items, covering different aspects of

Home Environment for Science Learning such as parents' help and

personal attention, the importance given to students' achievement to

his peers, parents' input in home assignments and discussions, parents'

control over their work habits and general behavior, and students'

freedom to work at his own pace and in his own style.

The subjects were asked to respond to each question by taking

against the entries of a three-point scale marked 'Always', 'Sometimes',

and 'Never'. The scoring procedure is as shown below:

Always - 2

Sometimes - I

Never - 0

VALIDITY AND RELIABILITY O F T H E INVENTORY

Validity

Criterion related validity of the test was estimated using average

class marks obtained in physics for 1st and 2nd terminal examination

of standard IX and intelligence (Non-verbal) treated as two criteria (for

N = 4 0 ) . The coefficient of correlat ion between home learning

environment score and average physics achievement score is 0.671.

The validity coefficient using Kerala Non-verbal Group Test of

Intelligence a s external criteria was 0 . 3 4 9 for the same sample

(for N=40).

Reliability

The internal consistency of the 'Home Environment Inventory for

Science Learning' determined by the Alpha coefficient is, 0.893.

The values of validity and reliability coefficients show that the tool

is a reasonably valid and reliable one for measuring Home Environment

for Science Learning.

A sample of the inventory is given as Appendix XIX.

4.4.8. SCIENCE LEARNING ENVIRONMENT INVENTORY (SLEI)

The different aspects of class room learning environment for science

learning-Science Learning Environment-student initiated and Science

Learning Environment-teacher provided-was measured by using 'Science

Learning Environment Inventory' developed and standardized by Suresh.

(Suresh, 1988).

This inventory contains 50 s ta tements , covering different

dimensions of science learning environment. Students' attentiveness,

students' social awareness, enjoyment of class, students' involvement

in class work and discussions, students' freedom to work at their own

pace and in their own style etc., are grouped under Science Learning

Environment -student initiated. Teacher's help and personal attention,

amount of stress placed on curricular and co-curricular activities, orderly

behaviour and organization of class, ' importance of students '

achievements to compare to that of their peers', difficulty of class work

and home assignments, teachers' control over students' work habits

and general behavior are grouped under 'Science Learning Environment-

teacher provided.

SCORING

The students are asked to respond to each question on a three

point scale- Always, Sometimes and Never. The score for each item

varied from 0 to 2. The weightages given for each item is shown below:

Positive item Negative item

Always - 2 Always - 0

Sometimes - 1 Sometimes - 1

Never - 0 Always - 2

RELIABILITY AND VALIDITY

The Alpha coefficient of homogeneity of the science Learning

Environment Inventory is 0.897. This index of homogeneity reveals

that all the items included in the questionnaire measure the same trait,

science learning environment.

The validity of the tool was established by validating it against the

total achievement in science subjects (physics, chemistry and biology)

for first and second terminal Examination of standard IX and also against

the Kerala Non-verbal Group Test of Intelligence. The validity coefficient

of the tool against the achievement in science subjects is 0 .587 (for

N=40) and that against the Non-verbal Group Test of Intelligence is

0 .385 (for N=40).

The validity and reliability coefficients indicate that the tool is

reasonably valid and reliable for measuring the Science Learning

Environment of Secondary school students.

A copy of the inventory is presented as Appendix XX

4.5.0. SAMPLE USED FOR THE STUDY

The population of the present study was secondary school students

(standard VIII, IX, and X) of Kerala. For the ease of preparing test of

process outcomes, the study was confined to students attending standard

IX of secondary schools of Kerala. Treating this as reference population,

the investigator had to take decisions regarding, size of the sample,

techniques of sampling, and factors to be represented in the sample.

The details are given below :

a) SIZE OF THE SAMPLE

Considering the special nature of the study and the type of statistical

procedures intended to be used, the size of the sample was tentatively

fixed as 1000 , eventhough, it is considerably larger than what was

suggested by social researchers for similar studies. The important

statistical procedures used for the study were.

1) Pearson's Product Moment Coefficient of Correlation 'r' to

estimate the association between the dependent variable-POP

- and each of the independent variables for the whole sample

and for subgroups HPA ,APA ,and LPA in POP.

2) Two-tailed test of significance of difference between means

for large independent groups.

3) Multiple regression equation to predict the POP, in terms of

independent variables, which have high correlation with the

dependent variable.

4) Multiple correlation coefficient 'R' to estimate the combined

effect of selected independent variables on the dependent

variable.

Size of the sample was such that, it should yield sufficiently large

subsamples for the different types of analysis. The question of

experimental mortality had to be considered. Also the possibility that

the investigator had to deal with individual student as the unit of study,

and the question of representing the factors which will yield a representa-

tive stratified sample had to be considered. Considering all these factors,

the size of the basal sample was dicided to keep around 1000.

b) SAMPLING TECHNIQUE

The population contains different strata of different sizes. Guilford

and Fruchter (1982) suggest "stratification is a step in the direction of

experimental control." A representative sample should contain individuals

drawn from each category, in accordance with the size of the group. So

proportionate stratified sampling technique was decided to be used

with individual student treated as the unit of testing for the present

study. This sampling technique was considered to be the best in view

of the highly heterogeneous nature of the sample.

C) FACTORS TO BE CONSIDERED FOR SELECTION OF THE SAMPLE

The widely accepted and popular procedure for stratification

recommended for the use of Indian social science researchers for studying

with school children, was adopted for the purpose of stratification.

According to this procedure, if representation is given for the following

basal variables, a most satisfactory representative sample of secondary

school pupils could be obtained.

The basal variables are:

1) sex of the subjects

2) rural/urban residence of the subject

3) instructional efficiency of the educational institution (roughly

estimated on the basis of pass percentage in the common

state examination at the end of the 10 years of schooling).

4) type of management of schools (govt. or private).

If these four basal variables are represented in the sample,it is

likely that other factors like cultural levels, socio- economic levels etc.,

get indirectly represented in the sample.

The official statistics kept by the Director of Public Instruction,

Government of Kerala was used for deciding the proport ionate

representation to be given for the four basal variables. The data for five

years, preceding the study was analyzed to obtain information regarding

the pupil enrolment, and pass percentage at the common secondary

school leaving certificate examination. The average figures for the five

years were taken up for estimating the proportions.

The estimated ratios were approximately as follows:

Boys : Girls = 9:10 (roughly)

Urban pupils : Rural pupils = 1:2 (roughly)

Pupils f rom government schools : Pupils f rom private

schools = 1:2

The five levels of pupils based on school efficiency,

A:B:C:D:E = 2:3:3:2:1

The letters A,B,C,D and E stand for the following level of

instructional efficiency.

Level A = Superior schools - pass percentage above 80 .

Level B = Above average schools -pass percentage below 8 0 and

above 60 .

Level C = Average schools - pass pe rcen tage below 6 0 and

above 40 .

Level D = Below average schools -pass percentage below 4 0 and

above 2 0

Level E = Inferior schools - pass percentage below 2 0

The approximate number of pupils to be covered from each

category was worked out, keeping in view the ratios fixed for each

category. A tentative break- up was roughly estimated on the assumption

that the total sample is 1000 and it will be covered by testing 2 4 class

divisions each with arround 4 5 pupils. This is represented in table 4 .7 .

TABLE 4.7. BREAK-UP OF THE TENTATIVE SAMPLE BASED ON SEX AND

PLACE OF RESIDENCE

The number of pupils fall in each efficiency level was estimated.

The values are given below.

Sex -

Boys

Girls

Total -

TABLE 4.8. NUMBER OF PUPILS SELECTED FOR THE SAMPLE FROM EACH

EFFICIENCY LEVEL OF THE SCHOOL

Urban

158

1 7 5

333

The approximate number of class divisions t o be covered is

estimated as 24 on the assumption that the strength of each class division

is 45. The schools were selected on the basis of the break-up given in

the table 4 . 7 and table 4.8.

Rural

316

35 1

6 6 7

LEVEL A

1 8 2

4.6.0 COLLECTION OF DATA

After selection and preparation of tools, and selection of sample,

the next phase to be accomplished was the collection of required data

from the sample by using the tools.

The investigator studied the basic literature relating to the tools

and test-booklets in detail to famiiiarise with the testing procedures and

possible eventualities before the commencement of the actual testing.

Total

4 7 4

5 2 6

1000

LEVEL C

2 7 3

LEVEL B

272

LEVEL D

182

LEVEL E

91

A schedule was prepared for the collection of data after visiting

the heads of the schools and teacher-in charge of the classes selected

for the collection of data. Their support was sought. The tools, test-

booklets and score sheets were got printed in adequate number.

The testing procedure followed a pre-fixed pattern in every school.

Firstly, the general data sheet was given to the subjects and got filled.

Then the TPOP was administered. After this an interval of 10 minutes

was allowed. Then the SATSL was administered. The next tool to be

used was SLII. The testing procedure for the fore-noon section was

over by the administration of SLII.

After lunch-break, The Kerala Non-verbal Group Test of Intelligence

was administered followed by Home Environment Inventory for Science

Learning (HEISL) and Science Learning Environment Inventory (SLEI).

The investigator herself visited the selected schools and collected

the data. Before administration of the tools, the aim and importance

of the study were explained to the students, for ensuring their active

participation and co-operation. Rules and procedure described already

were strictly followed in all schools for the uniformity of the testing

procedure.

While administering each test, the investigator was particular to

follow certain steps. They were:

1) distributing test-booklets together with instructions

2) explaining the directions given in the instruction

3) distributing the response sheets

4) making the students familiar with response sheet and mode

of entering responses

5) clearing the doubts of the students and giving directions

regarding time limit

6 ) collecting back the test booklets and response sheets

These steps were invariably followed in the administration of each

test. An interval of five minutes was given to the children before the

next tool, if they were administered consecutively.

4.7.0. SCORING AND CONSOLIDATION OF DATA

Scoring of the response sheets were done according to the

directions given in the test manuals and conventional procedures.

Punched cards were used for the scoring of The Kerala Non-

verbal Group Test of Intelligence, TPOP, and SLII in order t o speed

up scoring. During Scoring, incomplete entries were eliminated. Only

the data, which are complete in all respects were selected. This left the

investigator with 948 subjects. Further, 4 8 items were randomly rejected

to brind down the number to 900 , for convenience.

The school- wise break-up of the final sample is presented in table

4.9. The scores o n different tools and other data were tabulated

on a consolidated data sheet . The total sample was classified on

the basis of pre-determined basal variables, such a s gender, rural/

urban residence, type of management, and school efficiency. Each

subject was assigned a number and the whole data corresponding

TABLE 4.9. DETAILS OF THE SCHOOL-WISE BREAK-UP OF THE FINAL SAMPLE

S1.No. Name of the School

1. Govt. Girls H.S. Ettumanoor

2. St. Ann's H.S. Kurianadu

3. Holy Cross H.S. Cherpunkal

4. St. Thomas H.S. Thudanganad

5. St. Antony's H.S. Vellikulam

6. St. Augustin's H.S. Karimkunnam

7. St. Mary's B.H.S. Kuravilangad

8. St. Ma1y'sG.H.S. Kuravilangad

9. Sivapuram H.S. Sivapuram

10. St. Pauls's H.S. Valiyakumaramangalam

11. Govt. Model H.S. Calicut University Campus

12. St. George H.S. Aruvithura

13. St. George H.S. Koottickal

Locality

Rural

"

Typeof

School

Girls

Co-Edn.

Boys

Girls

Co-Edn.

Boys

Co-Edn.

Boys

Co-Edn.

No. of

Boys

-

20

18

14

25

27

28

-

11

34

30

34

17

Typeof

management

Govt

Private

"

Govt

Private

"

School

efficiency

Average

Superior

Above Avg.

Average

Below Avg.

,.

No. of Girls

40

18

22

16

25

26

-

35

22

-

20

-

19

Total

40

38

40

30

50

53

28

35

32

34

50

34

36

SI.No. Name of the School

14. KoothuparamhaH.S. Koothuparamha

15. Govt. V.H.S.S. Kadirur

16. Govt. H.S. Erattupetta

17. Govt. H.S. Thirurangadi

18. St. Thomas H.S. Pala

19. St. Augustine's H.S. Muvattupuzha

20. St.AntonySs H.S. Kacheripady

21. St. Mary's H.S. Ernakulam

22. St. Albert's H.S. Ernakulam

23. Govt. Model H.S. Muvattupuzha

24. Govt. G.H.S. Kaloor,

Total

- 2

Locality

Rural

Urban

,,

,,

,,

,,

,,

Type of School

Co-Edn.

,,

,,

,,

Boys

&Is

,,

,,

Boys

Co-Edn.

Girls

Type of

management

Private

Govt.

,,

Private

,,

,,

,,

,,

Govt.

Govt.

Schoof

efficiency

Below Avg.

,,

Inferior

Superior

,,

AboveAvg.

Average

Inferior

No. of

Boys

15

16

27

21

40

40

15

432

No. of

Girls

21

22

17

18

49

29

28

14

28

468

Total

36

38

44

39

40

49

29

28

40

29

28

900

to that subject was coded in different columns headed with suitable

codes to identify each, against the number.

The total group of 900 subjects was divided into High Process

Achievers (HPA), Average Process Achievers (APA), and Low Process

Achievers (LPA) with appropriate cut off in terms of the scores of the

total group in the dependent variable.

4.8.0 STATISTICAL TECHNIQUES USED

The following statistical techniques were employed for analysing,

interpreting and testing different hypotheses of the study.

a) Pearson's Product- moment Coefficient of Correlation 'r': This

was employed to study the association between the dependent

variable- POP- and each of the independent variables for the

whole sample and for the three subgroups Viz., HPA, APA,

and LPA.

b) Two-tailed Test of Significance of the difference between

means for large independent groups: This was used to compare

the three groups, (HPA-APA); (APA-LPA); and (HPA-LPA)

obtained on the basis of the scores in POP with respect to

each independent variable.

c) Multiple Regression Equation: This was developed to predict

POP in terms of a few select independent variables, which

have high correlation with the dependent variable.

d) Multiple Correlation Coefficient 'R ' . This was used to estimate

the combined effect of few select independent variables on

POP. Only those variables, which register high correlations

with the dependent variable, were used for this calculation.

4.9.0 DESCRIPTION OF THE STATISTICAL TECHNIQUES USED

a) Two-tailed test of significance of the difference between means

for large independent groups.

The ability of each of the independent variables- cognitive, affective

social, and environmental- to discriminate between the three groups of

POP - HPA, APA, and LPA - when taken in pairs (viz., HPA-APA;

APA-LPA; HPA-LPA) was determined by testing the significance of

the difference between means of these paired groups.

The procedure is to work out the t-values (critical ratios) given by

t = M, -M2 the formula

sE (MI - m) (Garrett, 1981)

where M, = Mean test score of the first group.

M, = Mean test score of the second group

and SE (MI-,,, = the standard error of the difference between

means MI and M,.

SE ,Ml*2, was estimated by using the formula

sE (Ml-t.12, = .\IsE'~, +sE',,

where SE & SE .,were the standard error of the mean scores

MI and M, respectively.

If N, and N, are the size of the samples under comparison and

o, and o, their respective standard deviations

0 1

then SE - - - m

The obtained t -value (critical ratio) was then treated as belonging

to a normal distribution. If the obtained 't' value falls between + 1. 9 6

and -1.96 the difference of means were treated as not being significant

at . 0 5 level. If the 't'-value falls outside the interval k 1.96, then the

difference between means was considered as significant at .05 level.

If the estimated 't'value falls inside the interval k 2 .58 , then the

difference between means was considered as not being significant at

.O1 level and if it falls outside the range k 2.58, it was considered as

significant.

b) Product moment coefficient of correlation.

Product momen t coefficient of co r r e l a t i on be tween two

variables x and y when they are given a s ungrouped pairs is

calculated by the formula

- - rxY

N C X Y - C X Z Y

J(NZX~ - ( Z X ) ~ ) (NZY~ - ( z Y ) ~ ) (Garrett, 1981)

where CX = Sum of all X scores

XY = sum of all Y scores

E X Y = sum of the product of the corresponding scores of X and Y

EX2 = sum of the squares of all X scores

CY2 = sum of the squares of all Y scores

The obtained correlation coefficients were interpreted by means

of the following approaches:

1) test of significance of the correlation coefficient

1 If the obtained correlation exceed -x1.96 or then it was JG

considered as significant at . 05 and .01 levels respectively

2) the .O1 confidence interval of 'r's

The limits of the . 0 1 confidence interval was estimated using the

formula r + - 2.58 SEr, where SEr is the standard error of 'r ' . SEr was

1 - r 2 calculated by using the formula, SEr = m where 'r' is the obtained

correlation

3) Verbal descriptions

Garrett's (1981) classification was used for the interpretation of

values of 'r ' ie., 'r ' from 0.0 to k 0.20 denotes indifferent or negligible

relationship.

' r ' from + .20 to + .40 denotes low correlation,

'r ' from + .40 to .70 denotes substantial or marked relationship.

'r' from + .70 to k 1.0 denotes very high relationship

4) Percen tage variance : This was est imated by finding out

rZ x 100; r being the obtained correlation coefficien (Fox, 1969) .

c ) MULTIPLE REGRESSION EQUATION

A multiple regression equation was derived to predict the

achievement of the students in POP by using four high influencing

independent variables.

The regression equation of X, (the criterion variable) on the

independent variable X,, X3, X4 and X5 in the deviation form is given by

- '1 12345) - b 1 2 . 345 '2 + b13.245 '3 + b14.235X4 + b15.234 '5.

(Garrett, 198 1)

In the score form the above equation becomes

Where b ~ ~ . 3 4 ~ , b13.2451 b14.2351 and b ~ ~ , , 3 4 a r e the regression

coefficients; MI, M,, M3, M4, M5 the mean scores on the variables

XI, X,, X3, X,, and X, respectively.

The regression coefficients are given by the formulae:

In these

The Coefficient of Multiple Correlation 'R'

T h e Multiple corre la t ion coefficient R of t h e variable

(r 1.2345 XI on variables X,,X,,X, and X, is given by Rl,,345, - - i r in

0 1

which s;,,,,is the standard deviation of the variable XI , when the effect

of the variables X,, X,, X, and X, are held constant.

The coefficient of multiple correlation indicates the strength of the

relationship between one variable and two or more others combined

with optimal weights.

Multiple 'R' is interpreted in the same way as simple correlation

' r ' . RZ, the coefficient of multiple determination tells us the proportion

of variance in the criterian variable; i.e. X,, that is dependent upon,

associated with or predicted by X,, X,, X, and X,, combined with the

regression weights used.

4.10.0 OTHER DETAILS RELATING T O T H E DESIGN

Procedure used for categorizing the whole sample in to groups

based on different levels of POP viz., High Process Achievers (HPA),

Average Process Achievers (APA), and Low Process Achievers (LPA) is

given below.

The total sample was divided into three groups on the basis of

scores obtained in the dependent variable POP For this, the scores of

the total sample of 900 subjects in POP was used in order to calculate

mean and standard deviation of the score distributions.

Assuming that M is the mean score and a the standard deviation

of 900 subjects in POP, the groups were labeled as below. A subject

whose score on the TPOP fell between (M + o) and (M -a) was classified

as Average Process Achiever (APA). A subject whose score was below

(M - a) was classified as Low Process Achiever (LPA). A subject whose

score was above (M + a) was classified as High Process Achiever (HPA).

The above Statistical techniques are made use of for the analysis

of data, the details of which are contained in a separate chapter-Chapter

V- Analysis, Interpretations, and discussion.